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The Eigenvectors of Single-spiked Complex Wishart Matrices: Finite and Asymptotic Analyses

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dc.contributor.author Dharmawansa, P
dc.contributor.author Dissanayake, P
dc.contributor.author Chen, Y
dc.date.accessioned 2023-06-14T03:54:47Z
dc.date.available 2023-06-14T03:54:47Z
dc.date.issued 2022
dc.identifier.citation Dharmawansa, P., Dissanayake, P., & Chen, Y. (2022). The Eigenvectors of Single-Spiked Complex Wishart Matrices: Finite and Asymptotic Analyses. IEEE Transactions on Information Theory, 68(12), 8092–8120. https://doi.org/10.1109/TIT.2022.3187919 en_US
dc.identifier.issn 0018-9448 en_US
dc.identifier.uri http://dl.lib.uom.lk/handle/123/21100
dc.description.abstract Let W 2 Cn n be a single-spiked Wishart matrix in the class W CWn(m; In + vvy) with m n, where In is the n n identity matrix, v 2 Cn 1 is an arbitrary vector with unit Euclidean norm, 0 is a non-random parameter, and ( )y represents the conjugate-transpose operator. Let u1 and un denote the eigenvectors corresponding to the smallest and the largest eigenvalues of W, respectively. This paper investigates the probability density function (p.d.f.) of the random quantity Z(n) ` = vyu` 2 2 (0; 1) for ` = 1; n. In particular, we derive a finite dimensional closed-form p.d.f. for Z(n) 1 which is amenable to asymptotic analysis as m; n diverges with m􀀀n fixed. It turns out that, in this asymptotic regime, the scaled random variable nZ(n) 1 converges in distribution to 2 2 =2(1 + ), where 2 2 denotes a chi-squared random variable with two degrees of freedom. This reveals that u1 can be used to infer information about the spike. On the other hand, the finite dimensional p.d.f. of Z(n) n is expressed as a double integral in which the integrand contains a determinant of a square matrix of dimension (n 􀀀 2). Although a simple solution to this double integral seems intractable, for special configurations of n = 2; 3, and 4, we obtain closed-form expressions. en_US
dc.language.iso en en_US
dc.publisher Institute of Electrical and Electronics Engineers en_US
dc.subject convergence in distribution en_US
dc.subject eigenvalues en_US
dc.subject eigenvectors en_US
dc.subject Gauss hypergeometric function en_US
dc.subject hypergeometric function of two matrix arguments en_US
dc.subject probability density function (p.d.f.) en_US
dc.subject single-spiked covariance en_US
dc.subject Wishart matrix en_US
dc.subject Laguerre polynomials en_US
dc.subject moment generating function (m.g.f.) en_US
dc.title The Eigenvectors of Single-spiked Complex Wishart Matrices: Finite and Asymptotic Analyses en_US
dc.type Article-Full-text en_US
dc.identifier.year 2022 en_US
dc.identifier.journal IEEE Transactions on Information Theory en_US
dc.identifier.issue 12 en_US
dc.identifier.volume 68 en_US
dc.identifier.database IEEE Xplore en_US
dc.identifier.pgnos 8092 - 8120 en_US
dc.identifier.email prathapa@uom.lk en_US
dc.identifier.email pasandissanayake@gmail.com en_US
dc.identifier.doi 10.1109/TIT.2022.3187919 en_US


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